import tensorflow as tf

class Model(object):
  def __init__(self, input, is_trainning, hidden_size, vocab_size, num_layers, dropout=0.5, init_scale=0.05):
    self.is_trainning = is_trainning
    self.input_obj = input
    self.batch_size = input.batch_size
    self.num_steps = input.num_steps
    self.hidden_size = hidden_size

    with tf.device("/cpu:0"):
      # 创建词向量 (word embedding), embedding 表示 Dense Vect密集向量
